AI-native development · Glossary term
What is Semantic Cache?
A cache that reuses a previous result when a new request is judged sufficiently similar under a chosen representation and threshold.
Why does Semantic Cache matter?
It can reduce latency and cost for repeated intents, but an incorrect match can return stale or user-inappropriate output.
Semantic Cache in practice
Cache low-risk FAQ answers by normalized intent, include tenant and policy version in the key, and bypass the cache for personalized or time-sensitive requests.
What is the common confusion about Semantic Cache?
Semantic similarity does not guarantee that two requests have the same correct answer. A semantic cache reuses a prior result, while prefix caching reuses exact-token KV state and prompt caching follows provider or application eligibility rules.
Learn Semantic Cache in the course
Lessons that name Semantic Cache in a title or section
- Caching, Rate Limiting & Cost Optimization
Most AI startups do not die from bad models. They die from bad unit economics. A single GPT-4o call costs fractions of a cent.
- Building a Production LLM Application
You have built prompts, embeddings, RAG pipelines, function calling, caching layers, and guardrails. Separately. In isolation. Like practicing guitar scales without ever playing a song.
Covered in Phase 11: LLM Engineering.
Related terms
- Prompt CacheReuse of provider-side or application-side computation for an identical or eligible prompt prefix so repeated inference avoids some…
- EmbeddingA learned mapping from discrete items (words, images, users) to dense vectors in continuous space, where similar items end up close together
- Cost per Successful TaskTotal system cost divided by the number of tasks that satisfy a defined success criterion, including retries, failed runs, tool use, and…
- GroundingConnecting a generated answer or action to evidence, state, or observations that the system can identify and check.
- Agent MemoryInformation stored outside the model and selected for use in later agent steps, such as prior decisions, user preferences, task episodes,…
- Prefix CachingReusing KV-cache blocks produced for an identical eligible token prefix across requests so the serving runtime can skip repeated prefix…
More terms in AI-native development
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